Emerging low-dimensional perovskite resistive switching memristors: from fundamentals to devices

With the exponential growth of the internet of things, artificial intelligence, and energy-efficient high-volume data digital communications, there is an urgent demand to develop new information technologies with high storage capacity. This needs to address the looming challenge of conventional Von Neumann architecture and Moore's law bottleneck for future data-intensive computing applications. A promising remedy lies in memristors, which offer distinct advantages of scalability, rapid access times, stable data retention, low power consumption, multistate storage capability and fast operation. Among the various materials used for active layers in memristors, low dimensional perovskite semiconductors with structural diversity and superior stability exhibit great potential for next generation memristor applications, leveraging hysteresis characteristics caused by ion migration and defects. In this review the progress of low-dimensional perovskite memory devices is comprehensively summarized. The working mechanism and fundamental processes, including ion migration dynamics, charge carrier transport and electronic resistance that underlies the switching behavior of memristors are discussed. Additionally, the device parameters are analyzed with special focus on the effective methods to improve electrical performance and operational stability. Finally, the challenges and perspective on major hurdles of low-dimensional perovskite memristors in the expansive application domains are provided.

Authors

Publication Details

Journal
Opto-Electronic Advances
Published
2025-01-01
DOI
https://doi.org/10.29026/oea.2025.240316
Citations
4
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
2.92
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Emerging low-dimensional perovskite resistive switching memristors: from fundamentals to devices

Hong Lian, Haifeng Ling, Shuanglong Wang, Hao Wu et al.
4 citations
Opto-Electronic Advances
Advanced Memory and Neural Computing
2.92
article

Emerging low-dimensional perovskite resistive switching memristors: from fundamentals to devices

Hong Lian, Haifeng Ling, Shuanglong Wang, Hao Wu, Tianxiao Xiao, Peter Müller‐Buschbaum, Yijia Huang
article en
4 citations

Abstract

With the exponential growth of the internet of things, artificial intelligence, and energy-efficient high-volume data digital communications, there is an urgent demand to develop new information technologies with high storage capacity. This needs to address the looming challenge of conventional Von Neumann architecture and Moore's law bottleneck for future data-intensive computing applications. A promising remedy lies in memristors, which offer distinct advantages of scalability, rapid access times, stable data retention, low power consumption, multistate storage capability and fast operation. Among the various materials used for active layers in memristors, low dimensional perovskite semiconductors with structural diversity and superior stability exhibit great potential for next generation memristor applications, leveraging hysteresis characteristics caused by ion migration and defects. In this review the progress of low-dimensional perovskite memory devices is comprehensively summarized. The working mechanism and fundamental processes, including ion migration dynamics, charge carrier transport and electronic resistance that underlies the switching behavior of memristors are discussed. Additionally, the device parameters are analyzed with special focus on the effective methods to improve electrical performance and operational stability. Finally, the challenges and perspective on major hurdles of low-dimensional perovskite memristors in the expansive application domains are provided.

Opto-Electronic AdvancesVol. 8(8)
Affordable and clean energy
Openalex Percentile: Top 8%
Advanced Memory and Neural Computing
2.92
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Emerging low-dimensional perovskite resistive switching memristors: from fundamentals to devices — Hong Lian, Haifeng Ling, et al. · Opto-Electronic Advances (2025) | TGRS Research Map | TGRS